Basic Convective and Mesoscale Research
Other Agency – The Role of a Dynamically-Balanced Dataset in Cloud Microphysics Parameterization Development
Funding Type: Office of Naval Research
Explore the effect of dataset selection on cloud microphysics parameterization.
A number of cloud microphysical parameterizations have been developed during the last decade using various datasets of cloud drop spectra. These datasets can be obtained either from observations, or artificially produced by some drop size spectra generator (e.g., by solving the coagulation equation under different input conditions), or obtained as output of an LES model that can predict explicitly cloud drop spectra. Each of the methods has its deficiencies. For example, observations are limited to the path of an airplane flight, while coagulation equation solutions depend on the input conditions. The crucial problem is to create a cloud drop spectra dataset which mimics realistic cloud drop parameters in nature. These parameters are closely related to the distribution of thermodynamical conditions and are difficult, if not impossible, to obtain a priori.
The best tool to recreate these conditions is with an LES model possessing explicit microphysics that can provide the full range of drop spectra generated by realistically represented turbulence. Exploring effects of dataset selection on obtained from this dataset cloud microphysical parameterization is the topic of the thesis work by the OU MS student Danielle Corrao. We simulated several cases of stratocumulus clouds observed during the Atlantic Stratocumulus Transition Experiment (ASTEX) field experiment in clean and polluted air masses. The simulated cloud layers represented cases with light (LD), moderate (MD) and heavy (HD) intensities of drizzle in the cloud. The results of the study showed high sensitivity of the derived parameterization on the selection of the dataset. We emphasize that the development of accurate parameterizations should require the use of dynamically balanced cloud drop spectra datasets.
This project is ongoing.